ObjectiveTo develop a predictive model and application for spontaneous passage of common bile duct stones using automated machine learning algorithms given the complexity of treatment decision-making for patients with common bile duct stones， and to reduce unnecessary endoscopic retrograde cholangiopancreatography （ERCP） procedures. MethodsA retrospective analysis was performed for the data of 835 patients who were scheduled for ERCP after a confirmed diagnosis of common bile duct stones based on imaging techniques in Changshu First People’s Hospital （dataset 1） and Changshu Traditional Chinese Medicine Hospital （dataset 2）. The dataset 1 was used for the training and internal validation of the machine learning model and the development of an application， and the dataset 2 was used for external testing. A total of 22 potential predictive variables were included for the establishment and internal validation of the LASSO regression model and various automated machine learning models. The area under the receiver operating characteristic curve （AUC）， sensitivity， specificity， and accuracy were used to assess the performance of models and identify the best model. Feature importance plots， force plots， and SHAP plots were used to interpret the model. The Python Dash library and the best model were used to develop a web application， and external testing was conducted using the dataset 2. The Kolmogorov-Smirnov test was used to examine whether the data were normally distributed， and the Mann-Whitney U test was used for comparison between two groups， while the chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups. ResultsAmong the 835 patients included in the study， 152 （18.20%） experienced spontaneous stone passage. The LASSO model achieved an AUC of 0.875 in the training set （n=588） and 0.864 in the validation set （n=171）， and the top five predictive factors in terms of importance were solitary common bile duct stones， non-dilated common bile duct， diameter of common bile duct stones， a reduction in serum alkaline phosphatase （ALP）， and a reduction in gamma-glutamyl transpeptidase （GGT）. A total of 55 models were established using automated machine learning， among which the gradient boosting machine （GBM） model had the best performance， with an AUC of 0.891 （95% confidence interval： 0.859‍ ‍—‍ ‍0.927）， outperforming the extreme randomized tree mode， the deep learning model， the generalized linear model， and the distributed random forest model. The GBM model had an accuracy of 0.855， a sensitivity of 0.846， and a specificity of 0.857 in the test set （n=76）. The variable importance analysis showed that five factors had important influence on the prediction of spontaneous stone passage， i.e.， were solitary common bile duct stones， non-dilated common bile duct， a stone diameter of <8 mm， a reduction in serum ALP， and a reduction in GGT. The SHAP analysis of the GBM model showed a significant increase in the probability of spontaneous stone passage in patients with solitary common bile duct stones， non-dilated common bile duct， a stone diameter of <8 mm， and a reduction in serum ALP or GGT. ConclusionThe GBM model and application developed using automated machine learning algorithms exhibit excellent predictive performance and user-friendliness in predicting spontaneous stone passage in patients with common bile duct stones. This application can help avoid unnecessary ERCP procedures， thereby reducing surgical risks and healthcare costs.

ObjectiveTo introduce a fixation technique with the modified levonorgestrel-releasing intrauterine system （LNG-IUS） and evaluate its efficacy in the treatment of adenomyosis patients with previous LNG-IUS expulsion. MethodsA retrospective analysis was done on 22 adenomyosis patients who underwent modified LNG-IUS fixation due to LNG-IUS expulsion at three hospitals from June 2022 to June 2023. The baseline clinical characteristics， operative and postoperative details were collected and analyzed. The Visual analogu scale （VAS） scores and pictorial blood loss assessment chart （PBAC） scores were measured and compared before， 3 and 6 months after the LNG-IUS fixation. ResultsThe mean operative time was （19.51±7.41） min and intraoperative bleeding was （6.71±5.30） mL. Of the patients， 13 were operated under local anaesthesia and the other 9 under intravenous anaesthesia. There were 4 operations performed by a resident doctor， 15 by an attending doctor and 3 by a senior doctor. No intraoperative or postoperative complication was found. The mean follow-up was 11.51 months and no patient had a recurrence of LNG-IUS expulsion during the follow-up period. The mean level of hemoglobin at 1 month after operation was significantly higher than that before （P<0.001）. VAS scores and PBAC scores at 3 and 6 months postoperatively were all improved significantly than those preoperatively （P<0.001）. ConclusionsEffectively preventing the recurrence of LNG-IUS expulsion， modified LNG-IUS fixation is a safe and efficient method for adenomyosis patients with previous LNG-IUS expulsion. Modified LNG-IUS fixation deserves the clinical application due to its easy operation and wide range of use on women.

Objective To propose a deep learning neural network approach for transforming megavoltage computed tomography(MVCT)images of cervical cancer into pseudo kilovoltage computed tomography(kVCT)images with high signal-to-noise ratio and contrast-to-noise ratio,thus providing three-dimensional anatomical images and localization information required for adaptive radiotherapy of cervical cancer,and guiding the accelerator to achieve precise treatment.Methods The MVCT and kVCT images of 54 patients treated with cervical cancer radiotherapy were collected,with 44 cases randomly selected as the training set,and the remaining 10 cases as the test set.A cyclic generative adversarial network with gating mechanism and multi-channel data input was used to synthesize pseudo-kVCT images from MVCT images.The network training results were evaluated with imaging quality evaluation parameters,such as mean absolute error(MAE),peak signal-to-noise ratio(PSNR),and structural similarity index(SSIM).Results The MAE,PSNR,and SSIM of MVCT imagesvspseudo-kVCT(5:5)images were(24.9±0.7)HUvs(17.8±0.3)HU,(29.8±0.2)dBvs(30.7±0.2)dB,and 0.841±0.007 vs 0.898±0.003,respectively.Conclusion The generated pseudo-kVCT images have advantages in noise reduction and contrast enhancement,and can reduce the need for additional MV-kVCT electron density calibration in dose calculations.The dose calculation ability of pseudo-kVCT is comparable to that of MVCT,providing a possibility for the application of pseudo-kVCT images in image-guided adaptive radiotherapy.

Objective To investigate the role and possible mechanism of curcumin(Cur)regulating Peroxiredoxin-6(Prdx6)expression in inhibiting Erastin-induced ferroptosis in C28/I2 chondrocytes.Methods Safranin O/Fast Green and hematoxylin-eosin(HE)staining were performed to observe the pathological changes in the knee joint of rats with osteoarthritis(OA).The expression levels of Prdx6 and GPX4 proteins in cartilage tissues with OA were detected by immunohistochemistry and Western blot.C28/I2 chondrocytes were treated with different concentrations of Cur,cell viability was detected by thiazolyl blue tetrazolium bromide(MTT)assay and cytotoxicity was measured by lactic dehydrogenase(LDH)assay.The production of lipid reactive oxygen species(ROS)in chondrocytes was detected by flow cytometry,and the total glutathione(GSH)assay kit was used to detect the GSH level in chondro-cytes.Western blot was performed to detect the expression level of Prdx6 and ferroptosis-related proteins in chon-drocytes.The interaction between the Cur molecule and Prdx6 was analyzed through the molecular docking tech-nique.Results During the OA progression,OA rats and OA patients showed pathological changes such as damage to the cartilage and a decrease in the number of chondrocytes.The expression levels of Prdx6 and GPX4 were re-duced in the cartilage tissues of OA patients compared with healthy people.Further study revealed that the treat-ment of Erastin-induced ferroptosis in C28/I2 chondrocytes in a mouse model with 20 μmol/L of Cur could improve cell viability,decrease cytotoxicity,inhibit lipid ROS production,and increase the level of intracellular GSH.Western blot results showed decreased expression of Prdx6,SLC7A11,FTH,and GPX4 and increased expression of ACSL4.In addition,Cur molecules interacted with Prdx6 protein by van der Waals forces and π bond.Conclu-sion Cur may inhibit Erastin-induced ferroptosis in C28/I2 chondrocytes by upregulating the Prdx6 expression lev-el.

Liver failure is a common end-stage liver disease syndrome in clinical practice characterized by massive necrosis of hepatocytes leading to rapid liver failure, and it is currently believed that excessive inflammation and immune response are the core mechanisms of this disease. Endogenous lipid mediators are involved in the regulation of a variety of inflammatory processes, including initiation, maintenance, and regression, and eicosanoids and pro-decomposition lipid mediators, as well as their complex metabolic pathways and transduction signals, play a key role in the regulation of these processes. This article reviews the key role of endogenous lipid mediators in the pathophysiological mechanism of inflammation and immune dysfunction in liver failure and the potential significance and new therapeutic opportunities of lipid immune pathway in liver failure, in order to provide new ideas for the clinical diagnosis and treatment of liver failure.

Inflammation is closely associated with the development of cancer. Tumor-associated macrophages (TAM) actively participate in tumor-related inflammation and promote tumor growth and metastasis, while under certain conditions, TAM also show cytotoxicity and tumor killing activity and thus inhibit the progression of cancer. Crosstalk between TAM and neighboring cells is closely associated with the progression of hepatocellular carcinoma (HCC) and drug resistance during treatment. This article summarizes the role of macrophages in HCC and the crosstalk between macrophages and other cells, so as to provide new strategies for the clinical diagnosis and treatment of HCC.

Objective:To establish an artificial intelligence robot-assisted diagnosis system for fundus diseases based on deep learning optical coherence tomography (OCT) and evaluate its application value.Methods:Diagnostic test studies. From 2016 to 2019, 25 000 OCT images of 25 000 patients treated at the Eye Center of the Second Affiliated Hospital of Zhejiang University School of Medicine were used as training sets and validation sets for the fundus intelligent assisted diagnosis system. Among them, macular epiretinal membrane (MERM), macular edema, macular hole, choroidal neovascularization (CNV), and age-related macular degeneration (AMD) were 5 000 sheets each. The training set and the verification set are 18 124 and 6 876 sheets, respectively. Through the transfer learning Attention ResNet structure algorithm, the OCT image was characterized by lesion identification, the disease feature was extracted by a specific procedure, and the given image was distinguished from other types of disease according to the statistical characteristics of the target lesion. The model algorithms of MERM, macular edema, macular hole, CNV and AMD were initially formed, and the fundus intelligent auxiliary diagnosis system of five models was established. The performance of each model-assisted diagnosis in the fundus intelligent auxiliary diagnostic system was evaluated by applying the subject working characteristic curve, area under the curve (AUC), sensitivity, and specificity.Results:With the intelligent auxiliary diagnosis system, the diagnostic sensitivity of the MERM was 93.5%, the specificity was 99.23%, and AUC was 0.983 7; the diagnostic sensitivity of macular edema was 99.02%, the specificity was 98.17%, and AUC was 0.994 6; the diagnostic sensitivity of macular hole was 98.91%, the specificity was 99.91%, AUC was 0.996 2; the diagnostic sensitivity of CNV was 97.54%, the specificity was 94.71%, AUC was 0.987 5; the diagnostic sensitivity of AMD was 95.12%, the specificity was 97.09%, AUC was 0.985 3.Conclusions:The artificial intelligence robot-assisted diagnosis system for fundus diseases based on deep learning for OCT images has accurate and efficient diagnostic performance for assisting the diagnosis of MERM, macular edema, macular hole, CNV, and AMD.

Glycolysis plays an important role in the development and progression of liver diseases and shows varying degrees of enhancement in different liver diseases, and it is closely associated with mitochondrial dysfunction (oxidative phosphorylation deficiency and reactive oxygen species production), which helps to fill energy production deficiency caused by impaired oxidative phosphorylation. Therefore, it might be possible to search for potential new therapies for liver diseases through targeted regulation of the key factors in aerobic glycolysis, such as hexokinase 2, pyruvate kinase M2, and other regulatory pathways. From the perspective of the association between glycolysis and liver diseases, this article elaborates on the therapeutic significance and potential value of glycolysis in liver diseases, in order to provide new ideas for the diagnosis and treatment of liver diseases.

Objective:To evaluate the effect of radical image-guided radiotherapy (IGRT) on the target dose in cervical cancer and investigate the appropriate application mode.Methods:Twenty patients with cervical cancer treated with helical tomotherapy (HT) in Seventh Medical Center of PLA General Hospital from 2012 to 2016 were selected. A megavoltage CT (MVCT) scan was performed before each treatment. The obtained MVCT images were used for dose parameter in the adaptive module of HT to obtain the actual dose (Plan 1) and the non-image-guided dose parameter was simulated (Plan 2). Each single dose distribution and the corresponding fused CT images were transferred to the software Mimvista 6.5 to obtain the total radiation dose parameter by dose superposition.Results:The motion of CTV, uterus and GTV in Plan 2 was significantly larger than that of Plan 1(all P<0.05), and the largest changes were seen in the ventrodorsal and uterine direction. The V 45Gy, V 50Gy, D 98% and D mean of CTV and uterus and V 50Gy of GTV in Plan 2 were significantly decreased compared with those in Plan 1(all P<0.05). The left-right motion of Plan 1 was negatively correlated with D 2% and D 98% of CTV and uterus (both P<0.05). The head-foot motion was negatively associated with V 45Gy and V 50Gy of GTV (both P<0.05). The ventrodorsal motion was negatively correlated with D 98% of uterus ( P<0.05). The left-right motion of Plan 2 was negatively correlated with D 2% of CTV and V 50Gy of uterus (both P<0.05). The head-foot motion was negatively associated with D 98% of CTV, and D 98%, D mean, V 45Gy and V 50Gy of uterus (all P<0.05). The ventrodorsal motion was negatively correlated with D 98% of CTV, D 98%, D mean, V 45Gy and V 50Gy of uterus, and D mean and V 45Gy of GTV (all P<0.05). Conclusions:In intensity-modulated radiotherapy for cervical cancer, the uterine body displacement is large and the low CTV area is mainly located in the uterine body. IGRT can significantly reduce the dosimetric deviation induced by organ movement.

Objective:To evaluate the changes of fetal renal artery blood flow parameters in fetuses with isolated borderline oligohydramnios (IBO) in the middle and third trimesters by Doppler ultrasound, and to assess its correlations with maternal and infant pregnancy outcomes.Methods:Twenty-seven IBO fetuses (IBO group) and 27 gestational age-matched normal fetuses (control group) from April to October 2019 in the Second Xiangya Hospital of Central South University underwent prenatal ultrasound examination during the middle and third trimesters. Renal artery blood flow parameters, including renal artery pulsatility index (RAPI), volume corrected renal artery pulsatility index (vcRAPI) and pregnancy outcomes were measured and compared between the two groups. Once diagnosed IBO, patients were recommended to the obstetric clinic for consultation and intervention. The correlation between RAPI, vcRAPI measured before intervention and prepartum amniotic fluid volume and pregnancy outcomes was analyzed, the ROC curve was plotted to find the better predictor.Results:The vcRAPI of the IBO group was higher than that of the control group ( P=0.015). In the IBO group, the vcRAPI measured before intervention was higer in those fetuses who were still IBO before delivery( P=0.048). In the IBO group, the correlation of the vcRAPI measured before intervention and IBO before delivery was statistically significant ( OR=2.41, 95% CI=1.06-5.43, P=0.035). The ROC curve showed that the sensitivity of vcRAPI to IBO was 0.67, the specificity was 0.75( P=0.002). Conclusions:Compared with RAPI, The vcRAPI may reflect the increase in fetal renal artery perfusion resistance of IBO group more timely. The higher vcRAPI before intervention in the IBO group have difficulty in recovering amniotic fluid volume before delivery.Increased vcRAPI is a better predictor of IBO before delivery.